Younggwang Kim

Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity

Hui Kwon Kim, Seonwoo Min, Myungjae Song et al. · Nature Biotechnology · 2018 · 371 citations · Full text

Molecular Biology, Gene Editing, Genome Editing +4

SpCas9 activity prediction by DeepSpCas9, a deep learning–based model with high generalization performance

Hui Kwon Kim, Younggwang Kim, Sungtae Lee et al. · Science Advances · 2019 · 234 citations · Full text

Engineering, Machine Learning, Genetics +25

High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells

Hui Kwon Kim, Sungtae Lee, Younggwang Kim et al. · Nature Biomedical Engineering · 2020 · 137 citations · Full text

Bioinformatics, Off-target Effect, Human Cells +12

Sequence-specific prediction of the efficiencies of adenine and cytosine base editors

Myungjae Song, Hui Kwon Kim, Sungtae Lee et al. · Nature Biotechnology · 2020 · 131 citations · Full text

Dna Sequencing, Functional Genomics, Engineering +12

High-throughput functional evaluation of human cancer-associated mutations using base editors

Younggwang Kim, Seung‐Ho Lee, Soohyuk Cho et al. · Nature Biotechnology · 2022 · 67 citations · Full text

Radiation Oncology, Engineering, Somatic Variant +13